{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T06:40:55Z","timestamp":1773297655678,"version":"3.50.1"},"reference-count":42,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2016,6,1]],"date-time":"2016-06-01T00:00:00Z","timestamp":1464739200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Clinical Cardiology"],"published-print":{"date-parts":[[2016,9]]},"abstract":"ABSTRACT<\/jats:title>Background<\/jats:title>Chronic Kidney Disease Epidemiology Collaboration (CKD\u2010EPI<\/jats:styled-content>) equations estimate glomerular filtration rate (GFR<\/jats:styled-content>) more accurately than the Modification of Diet in Renal Disease (MDRD<\/jats:styled-content>) equation.<\/jats:p><\/jats:sec>Hypothesis<\/jats:title>New CKD\u2010EPI equations improve risk stratification in patients with non\u2010ST\u2010segment elevation acute coronary syndrome (NSTE\u2010ACS) and provide complementary information to the Global Registry of Acute Coronary Events (GRACE) risk score.<\/jats:p><\/jats:sec>Methods<\/jats:title>We studied 350 subjects (mean age, 68 \u00b1 12 years; 70% male) with NSTE\u2010ACS<\/jats:styled-content>. Estimated GFR<\/jats:styled-content> was calculated using the MDRD<\/jats:styled-content> and new CKD\u2010EPI<\/jats:styled-content> equations based on serum creatinine (SCr<\/jats:styled-content>) and\/or cystatin C (CysC<\/jats:styled-content>) concentrations obtained within 48 hours of hospital admission. The primary endpoint was all\u2010cause death during follow\u2010up.<\/jats:p><\/jats:sec>Results<\/jats:title>Over the study period (median, 648 days [interquartile range, 236\u20131042 days]), 31 patients died (0.05% events per person\u2010year). Decedents had poorer renal\u2010function parameters (P<\/jats:italic> < 0.001). Both CysC<\/jats:styled-content>\u2010based CKD\u2010EPI<\/jats:styled-content> equations had the highest areas under the receiver operating characteristic curve for the prediction of all\u2010cause mortality. After multivariate adjustment, only CysC<\/jats:styled-content>\u2010based CKD\u2010EPI<\/jats:styled-content> equations were independent predictors of all\u2010cause mortality (CKD\u2010EPISCr<\/jats:sub><\/jats:styled-content>\u2010<\/jats:sub>CysC<\/jats:sub><\/jats:styled-content>, per mL<\/jats:styled-content>\/min\/1.73 m2<\/jats:sup>: hazard ratio: 0.975, 95% confidence interval: 0.956\u20100.994, P<\/jats:italic> = 0.009; CKD\u2010EPICysC<\/jats:sub><\/jats:styled-content>, per mL<\/jats:styled-content>\/min\/1.73 m2<\/jats:sup>: hazard ratio: 0.976, 95% confidence interval: 0.959\u20100.993, P<\/jats:italic> = 0.005). Reclassification analyses showed that only CysC<\/jats:styled-content>\u2010based CKD\u2010EPI<\/jats:styled-content> equations improved predictive accuracy of the GRACE<\/jats:styled-content> risk score.<\/jats:p><\/jats:sec>Conclusions<\/jats:title>In patients with NSTE\u2010ACS<\/jats:styled-content>, CysC<\/jats:styled-content>\u2010based CKD\u2010EPI<\/jats:styled-content> equations improved clinical risk stratification for mortality and added complementary prognostic information to the GRACE<\/jats:styled-content> risk score.<\/jats:p><\/jats:sec>","DOI":"10.1002\/clc.22556","type":"journal-article","created":{"date-parts":[[2016,6,2]],"date-time":"2016-06-02T01:02:45Z","timestamp":1464829365000},"page":"507-515","source":"Crossref","is-referenced-by-count":17,"title":["Comparison of Risk Prediction With the CKD\u2010EPI<\/scp> and MDRD<\/scp> Equations in Non\u2013ST<\/scp>\u2010Segment Elevation Acute Coronary 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